Access to consistent, high-quality metadata is critical to finding, understanding, and reusing scientific data. However, while there are many relevant vocabularies for the annotation of a dataset, none sufficiently captures all the necessary metadata. This prevents uniform indexing and querying of dataset repositories. Towards providing a practical guide for producing a high quality description of biomedical datasets, the W3C Semantic Web for Health Care and the Life Sciences Interest Group (HCLSIG) identified Resource Description Framework (RDF) vocabularies that could be used to specify common metadata elements and their value sets. The resulting guideline covers elements of description, identification, attribution, versioning, provenance, and content summarization. This guideline reuses existing vocabularies, and is intended to meet key functional requirements including indexing, discovery, exchange, query, and retrieval of datasets, thereby enabling the publication of FAIR data. The resulting metadata profile is generic and could be used by other domains with an interest in providing machine readable descriptions of versioned datasets.

Company data, ranging from basic company information such as company name(s) and incorporation date to complex balance sheets and personal data about directors and shareholders, are the foundation that many data value chains depend upon in various sectors (e.g., business information, marketing and sales, etc.). Company data becomes a valuable asset when data is collected and integrated from a variety of sources, both authoritative (e.g., national business registers) and non-authoritative (e.g., company websites). Company data integration is however a difficult task primarily due to the heterogeneity and complexity of company data, and the lack of generally agreed upon semantic descriptions of the concepts in this domain. In this article, we introduce the euBusinessGraph ontology as a lightweight mechanism for harmonising company data for the purpose of aggregating, linking, provisioning and analysing basic company data. The article provides an overview of the related work, ontology scope, ontology development process, explanations of core concepts and relationships, and the implementation of the ontology. Furthermore, we present scenarios where the ontology was used, among others, for publishing company data (business knowledge graph) and for comparing data from various company data providers. The euBusinessGraph ontology serves as an asset not only for enabling various tasks related to company data but also on which various extensions can be built upon.

The Galleries, Libraries, Archives and Museums (GLAM) sector deals with complex and varied data. Integrating that data, especially across institutions, has always been a challenge. Semantic data integration is the best approach to deal with such challenges. Linked Open Data (LOD) enable large-scale Digital Humanities (DH) research, collaboration and aggregation, allowing DH researchers to make connections between (and make sense of) the multitude of digitized Cultural Heritage (CH) available on the web. An upsurge of interest in semtech and LOD has swept the CH and DH communities. An active Linked Open Data for Libraries, Archives and Museums (LODLAM) community exists, CH data is published as LOD, and international collaborations have emerged. The value of LOD is especially high in the GLAM sector, since culture by its very nature is cross-border and interlinked. We present interesting LODLAM projects, datasets, and ontologies, as well as Ontotext's experience in this domain. An extended version of this paper is available. It has 77 pages, 67 figures, detailed info about CH content and XML standards, Wikidata and global authority control.

Knowledge organization systems (KOS) can use different types of hierarchical relations: broader generic (BTG), broader partitive (BTP), and broader instantial (BTI). The latest ISO standard on thesauri (ISO 25964) has formalized these relations in a corresponding OWL ontology (De Smedt et al., ISO 25964 part 1: thesauri for information retrieval: RDF/OWL vocabulary, extension of SKOS and SKOS-XL. http://​purl.​org/​iso25964/​skos-thes , 2013 ) and expressed them as properties: broaderGeneric, broaderPartitive, and broaderInstantial, respectively. These relations are used in actual thesaurus data. The compositionality of these types of hierarchical relations has not been investigated systematically yet. They all contribute to the general broader (BT) thesaurus relation and its transitive generalization broader transitive defined in the SKOS model for representing KOS. But specialized relationship types cannot be arbitrarily combined to produce new statements that have the same semantic precision, leading to cases where inference of broader transitive relationships may be misleading. We define Extended properties (BTGE, BTPE, BTIE) and analyze which compositions of the original “one-step” properties and the Extended properties are appropriate. This enables providing the new properties with valuable semantics usable, e.g., for fine-grained information retrieval purposes. In addition, we relax some of the constraints assigned to the ISO properties, namely the fact that hierarchical relationships apply to SKOS concepts only. This allows us to apply them to the Getty Art and Architecture Thesaurus (AAT), where they are also used for non-concepts (facets, hierarchy names, guide terms). In this paper, we present extensive examples derived from the recent publication of AAT as linked open data.

This paper gives an overview of existing applications of Linear Logic (LL) to issues of computation. Alter a substantial introduction to LL, it discusses the implications of LL to functional programming, logic programming, concurrent and object-oriented programming and some other applications of LL, like semantios of negation in LP, non-monotonic issues in AI planning, etc. Although the overview covers pretty much the state-of-the-art in this area, by necessity many of the works are only mentioned and referenced, but not discussed in any considerable detail. The paper does not presuppose any previous exposition to LL, and is addressed more to computer scientists (probably with a theoretical inclination) than to logicians. The paper contains over 140 references, of which some 80 are about applications of LL.